AUTHOR=Cai Jingyi , Li Chaoyuan , Li Shun , Yi Jianru , Wang Jun , Yao Ke , Gan Xinyan , Shen Yu , Yang Pu , Jing Dian , Zhao Zhihe 

TITLE=A Quartet Network Analysis Identifying Mechanically Responsive Long Noncoding RNAs in Bone Remodeling

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.780211

DOI=10.3389/fbioe.2022.780211

ISSN=2296-4185

ABSTRACT=Mechanical force, so ubiquitous that often taken for granted and overlooked, is now gaining spotlights for reams of evidence corroborating their crucial roles in living body. Bone, particularly, experiences manifold extraneous force like strain and compression, as well as the intrinsic cues like fluid shear stress and physical properties of the microenvironment. Though sparkled in diversified background, long non-coding RNAs (lncRNAs) concerning the mechano-transduction process that bone undergoes, are not yet detailed in a systematic way. Our principal goal in this research is to highlight the potential lncRNA-focused mechanical signaling systems which may be adapted by bone-related cells for biophysical environment responding. Based on credible lists of force-sensitive mRNAs and miRNAs, we constructed a force-responsive competing endogenous RNA network for lncRNA identification. To elucidate the underlying mechanism, we then illustrated the possible crosstalk between lncRNAs and mRNAs, transcriptional factor, as well as mapped lncRNAs to known signaling pathways involved in bone remodeling and mechano-transduction. Last, we developed combinative analysis between predicted and established lncRNAs, constructing a pathway-lncRNA network which suggests interactive relationships and new roles of known factors as H19. In conclusion, our work provided a systematic quartet network analysis, uncovered candidate force-related lncRNAs and highlighted both the upstream and downstream processes that possibly involved. A new mode of bioinformatic analysis integrating sequencing data, literature retrieval and computational algorithm were also introduced. Hopefully, our work would provide a moment of clarity against the multiplicity and complexity of lncRNA world confronting mechanical input.